9 Repositories
Python gait Libraries
This is the code for the paper "Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei: Gait Recognition in the Wild with Dense 3D Representations and A Benchmark. (CVPR 2022)"
Gait3D-Benchmark This is the code for the paper "Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei: Gait Recognition in the Wild
"Learning Free Gait Transition for Quadruped Robots vis Phase-Guided Controller"
PhaseGuidedControl The current version is developed based on the old version of RaiSim series, and possibly requires further modification. It will be
Tools for the Cleveland State Human Motion and Control Lab
Introduction This is a collection of tools that are helpful for gait analysis. Some are specific to the needs of the Human Motion and Control Lab at C
Python package for analyzing sensor-collected human motion data
Python package for analyzing sensor-collected human motion data
Learning multiple gaits of quadruped robot using hierarchical reinforcement learning
Learning multiple gaits of quadruped robot using hierarchical reinforcement learning We propose a method to learn multiple gaits of quadruped robot us
A flexible and extensible framework for gait recognition.
A flexible and extensible framework for gait recognition. You can focus on designing your own models and comparing with state-of-the-arts easily with the help of OpenGait.
OpenGait is a flexible and extensible gait recognition project
A flexible and extensible framework for gait recognition. You can focus on designing your own models and comparing with state-of-the-arts easily with the help of OpenGait.
A tiny, friendly, strong baseline code for Person-reID (based on pytorch).
Pytorch ReID Strong, Small, Friendly A tiny, friendly, strong baseline code for Person-reID (based on pytorch). Strong. It is consistent with the new
TraND: Transferable Neighborhood Discovery for Unsupervised Cross-domain Gait Recognition.
TraND This is the code for the paper "Jinkai Zheng, Xinchen Liu, Chenggang Yan, Jiyong Zhang, Wu Liu, Xiaoping Zhang and Tao Mei: TraND: Transferable